jblas is a fast linear algebra library for Java. jblas is based on BLAS and LAPACK, the de-facto industry standard for matrix computations, and uses state-of-the-art implementations like ATLAS for all its computational routines, making jBLAS very fast.

jblas can is essentially a light-wight wrapper around the BLAS and LAPACK routines. These packages have originated in the Fortran community which explains their archaic API. On the other hand modern implementations are hard to beat performance wise. jblas aims to make this functionality available to Java programmers such that they do not have to worry about writing JNI interfaces and calling conventions of Fortran code.

jblas is the only actively developed matrix library which is based on native implementations (The other such project is netlib-java which is apparently not maintained anymore). Therefore, jblas is much faster than other projects, in particular for large complex tasks like matrix-matrix multiplication, solving linear equations, or eigenproblems.

Build process can now generate different kinds of jar files, and also
generate shared libraries which are statically linked against BLAS,
LAPACK or ATLAS. You can also generate a multiplatform jar file which
contains shared libraries for different platforms.

Generated wrapper code has been optimized a bit:

in the lapack wrapper with automatic workspace allocation, only
small dummy arrays are passed in the workspace query, meaning that
the real arrays are only passed once, not twice.

The wrapper now also parses information whether output variables
are input or output and releases the arrays with JNI_ABORT in case
they are not output variables. This should also reduce the amount
of copying.